Flattening the curves: on-off lock-down strategies for COVID-19 with an application to Brazil

The current COVID-19 pandemic is affecting different countries in different ways. The assortment of reporting techniques alongside other issues, such as underreporting and budgetary constraints, makes predicting the spread and lethality of the virus a challenging task. This work attempts to gain a b...

Full description

Saved in:
Bibliographic Details
Published inJournal of mathematics in industry Vol. 11; no. 1; p. 2
Main Authors Tarrataca, Luís, Dias, Claudia Mazza, Haddad, Diego Barreto, De Arruda, Edilson Fernandes
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 06.01.2021
Springer Nature B.V
SpringerOpen
Subjects
Applications of Mathematics
Coronavirus
Coronaviruses
COVID-19
economics and technology
industry
Lethality
Lockdown
Math. Appl. in Environmental Science
Mathematical and Computational Biology
Mathematical and Computational Engineering
Mathematical Methods in Physics
Mathematical Modeling and Industrial Mathematics
Mathematical models of the spread and consequences of the SARS-CoV-2 pandemics. Effects on health
Mathematics
Mathematics and Statistics
Neural network
Quarantine
Seir models
society
Viruses
Brazil
COVID-19
Quarantine
Lockdown
Coronavirus
Neural network
Seir models
Online AccessGet full text

Cover

More Information
Summary:The current COVID-19 pandemic is affecting different countries in different ways. The assortment of reporting techniques alongside other issues, such as underreporting and budgetary constraints, makes predicting the spread and lethality of the virus a challenging task. This work attempts to gain a better understanding of how COVID-19 will affect one of the least studied countries, namely Brazil. Currently, several Brazilian states are in a state of lock-down. However, there is political pressure for this type of measures to be lifted. This work considers the impact that such a termination would have on how the virus evolves locally. This was done by extending the SEIR model with an on / off strategy. Given the simplicity of SEIR we also attempted to gain more insight by developing a neural regressor. We chose to employ features that current clinical studies have pinpointed has having a connection to the lethality of COVID-19. We discuss how this data can be processed in order to obtain a robust assessment.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2190-5983
2190-5983
DOI:10.1186/s13362-020-00098-w